Wyniki wyszukiwania dla: STRUCTURE PREDICTION
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Influence of pitting corrosion on fatigue and corrosion fatigue of ship and offshore structures. Part II: Load - pit crack interaction
PublikacjaIn the paper has been discussed influence of stresses on general corrosion rate and corrosion pit nucleation and growth rate, whose presence has been questioned by some authors but accepted by most of them. Influence of pit walls roughness on fatigue life of a plate suffering pit corrosion and presence of so called "non damaging" pits which never lead to initiation of fatigue crack, has been presented. Possibility of prediction...
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Study of Noise Propagation for Small Vessels
PublikacjaThe paper presents the results of the noise propagation analysis in ship structures tested in a number of AHTS (Anchor Handling Tug Supply) vessels. Statistical Energy Analysis (SEA) based on numerical model developed specially for the purpose of this numerical investigation were conducted. This numerical model enabled the analysis of both the structural elements and the acoustic spaces. For the detailed studies 47 points fixed...
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Ionosphere variability I: Advances in observational, monitoring and detection capabilities
PublikacjaThe paper aims to review recent advances regarding the observational and monitoring capabilities of the ionization conditions in the Earth's upper atmosphere. The analysis spans both ground and space-based experiments, seeking for new installations and/or missions, new or upgraded instrumentation and/or observational network establishments as means for advancing current understanding and prediction ability of the ionosphere variability....
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Outlier detection method by using deep neural networks
PublikacjaDetecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....
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Accuracy of Pretreatment Ultrasonography Assessment of Intra-Abdominal Spread in Epithelial Ovarian Cancer: A Prospective Study
PublikacjaThe aim of this study was to test the accuracy of ultrasonography performed by gynecological oncologists for the preoperative assessment of epithelial ovarian cancer (EOC) spread in the pelvis and abdominal cavity. A prospective, observational cohort study was performed at a single tertiary cancer care unit. Patients with suspected EOC were recruited and underwent comprehensive transvaginal and abdominal ultrasonography performed...
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Long-term hindcast simulation of sea ice in the Baltic Sea
Dane BadawczeThe data set contains the results of numerical modeling of sea ice over a period of 50 years (1958-2007) in the Baltic Sea. A long-term hindcast simulation was performed using a three-dimensional hydrodynamic model PM3D (Kowalewski and Kowalewska-Kalkowska, 2017), a new version of the M3D model (Kowalewski, 1997). A numerical dynamic-thermodynamic model...
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublikacjaThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Viscoplastic damage analysis of structures subjected to impact loading. Plate and shell structures. - Ł. Pyrzowski.
PublikacjaThe work presents the investigation in the response of plate-shell structures subjected to impact loading (gas mixture explosions). This phenomenon is studied in the context of its mechanical aspects, mainly the ductile fracture prediction. The work starts with the literature review and the description of theories, which are nowadays the most popular in the damage and failure modelling. After selecting the theoretical models and...
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Investigation of the road noise source employing an automatic noise monitoring station
PublikacjaThe paper presents a pilot investigation of noise source models in two selected localizations in the context of future dynamic noise map creation. The experiments were carried out using the automatic noise monitoring station engineered at the Multimedia Systems Departmentof the Gda´nsk University of Technology. The results of the noise measurements employing monitoring stations and its comparison to the reference values are depicted....
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DO WE NEED NAVIER NUMBER? – FURTHER REMARKS AND COMPARISON WITH ANOTHER DIMENSIONLESS NUMBERS
PublikacjaThis paper presents a role of the Navier number (Na-dimensionless slip-length) in universal modelling of flow reported in micro- and nano-channels like: capillary biological flows, fuel cell systems, micro-electro-mechanical systems and nano-electro-mechanical systems. Similar to another bulk-like and surface-like dimensionless numbers, the Na number should be treated as a ratio of internal viscous to external viscous momentum...
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COMPARISON OF TWO MODELS OF CONDENSATION
PublikacjaIn the low-pressure part of steam turbine, the state path usually crosses the saturation line in penultimate stages. At least last two stages of this part of turbines operate in two –phase region. The liquid phase in this region in mainly created in the process of homogeneous and heterogeneous condensation. Several observations confirm however, that condensation often occurs earlier than it is predicted by theory i.e. before the...
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Remarks on steam condensation modeling related to steam turbine large output
PublikacjaIn the paper numerical simulations have been performed to predict the performance of the diferent steam models. All of the considered models of steam condensation have been validated on the base of benchmark experiment employing expansion in nozzle and next on the low pressure part of the steam turbine equipped with the so-called Baumann stage. For numerical analysis three models have been finally used - the ideal steam model without...
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Sparse autoregressive modeling
PublikacjaIn the paper the comparison of the popular pitch determination (PD) algorithms for thepurpose of elimination of clicks from archive audio signals using sparse autoregressive (SAR)modeling is presented. The SAR signal representation has been widely used in code-excitedlinear prediction (CELP) systems. The appropriate construction of the SAR model is requiredto guarantee model stability. For this reason the signal representation...
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Introduction to the special issue on machine learning in acoustics
PublikacjaWhen we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...
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INFLUENCE OF THE HULL SHAPE ON THE ENERGY DEMAND OF A SMALL INLAND VESSEL WITH HYBRID PROPULSION
PublikacjaRecently, there has been a significant development of ecological propulsion systems, which is in line with the general trend of environmentally friendly “green shipping”. The main aim is to build a safe, low-energy passenger ship with a highly efficient, emission-free propulsion system. This can be achieved in a variety of ways. The article presents the main problems encountered by designers and constructors already at the stage...
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Estimation of Housing Demand with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
PublikacjaIt has always been important to anticipate the demand for a product. To determine the demand for any product, the parameters such as the economic situation and the demands of the rival products are used generally. Especially in the housing sector, which is the locomotive sector for emerging countries, it is critical to anticipate housing demand and its relationship with economic variables. Because of that, economists, real estate...
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AVHRR Level1CD covering Baltic Sea area year 2006
Dane BadawczeThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2010
Dane BadawczeThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2007
Dane BadawczeThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2011
Dane BadawczeThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2012
Dane BadawczeThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2008
Dane BadawczeThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2009
Dane BadawczeThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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Framework for Integration Decentralized and Untrusted Multi-vendor IoMT Environments
PublikacjaLack of standardization is highly visible while we use historical data sets or compare our model with others that use IoMT devices from different vendors. The problem also concerns the trust in highly decentralized and anonymous environments where sensitive data are transferred through the Internet and then are analyzed by third-party companies. In our research we propose a standard that has been implemented in the form of framework...
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Evaluation of the Electronic Nose Used for Monitoring Environmental Pollution
PublikacjaAir pollution is a one of the major concern of civilized world, which has a significant impact on human health and the environment. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring. Electronic-nose systems based on sensors are an interesting and promising technology in...
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Qualitative and Quantitative Analysis of Selected Tonic Waters by Potentiometric Taste Sensor With All-Solid-State Electrodes
PublikacjaTaste sensor with five all-solid-state electrodes (ASSE) III (third version) was used for qualitative and quantitative analysis of selected tonic waters (J.Gasco, Kinley, Jurajski, Jurajski with citrus flavor, Carrefour, Schweppes Indian Tonic, and Schweppes Bitter Lemon). The results obtained by this taste sensor analyzed with principal component analysis, agglomerative hierarchical clustering methods show that this sensor can...
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Accurate modeling of quasi-resonant inverter fed IM drive
PublikacjaIn this paper wide-band modeling methodology of a parallel quasi-resonant dc link inverter (PQRDCLI) fed induction machine (IM) is presented. The modeling objective is early-design stage prediction of conductive electromagnetic interference (EMI) emissions of the considered converter fed IM drive system. Operation principles of the selected topology of PQRDCLI feeding IM drive are given. Modeling of the converter drive system is...
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IFE: NN-aided Instantaneous Pitch Estimation
PublikacjaPitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...
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Automatic recognition of therapy progress among children with autism
PublikacjaThe article presents a research study on recognizing therapy progress among children with autism spectrum disorder. The progress is recognized on the basis of behavioural data gathered via five specially designed tablet games. Over 180 distinct parameters are calculated on the basis of raw data delivered via the game flow and tablet sensors - i.e. touch screen, accelerometer and gyroscope. The results obtained confirm the possibility...
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Determination of Odour Interactions of Three-Component Gas Mixtures Using an Electronic Nose
PublikacjaThe paper presents an application of an electronic nose prototype comprised of six TGS-type sensors and one PID-type sensor to identify odour interaction phenomena in odorous three-component mixtures. The investigation encompassed eight odorous mixtures—toluene-acetone-triethylamine and formaldehyde-butyric acid-pinene — characterized by different odour intensity and hedonic tone. A principal component regression (PCR) calibration...
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Burnout Investigation of Small Diameter Tubes Immersed in Nanofluids
PublikacjaThis paper deals with research into pool boiling critical heat flux (CHF) of water–Al2O3, water–TiO2 and water–Cu nanofluids on horizontal stainless steel tubes. The experiments were conducted under atmospheric pressure. Nanoparticles were tested at concentrations of 0.001%, 0.01%, 0.1% and 1% by weight. Ultrasonic vibration was used in order to stabilize the dispersion of the nanoparticles. Although dispersants were not used to...
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Autonomous Ship Utility Model Parameter Estimation Utilising Extended Kalman Filter
PublikacjaIn this paper, a problem of autonomous ship utility model identification for control purposes is considered. In particular, the problem is formulated in terms of model parameter estimation (one-step-ahead prediction). This is a complex task due to lack of measurements of the parameter values, their time-variability and structural uncertainty introduced by the available models. In this work, authors consider and compare two utility...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublikacjaThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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Application Isssues of the Semi-Markov Reliability Model
PublikacjaPredicting the reliability of marine internal combustion engines, for instance, is of particular importance, as it makes it possible to predict their future reliability states based on the information on the past states. Correct reliability prediction is a complex process which consists in processing empirical results obtained from operating practice, complemented by analytical considerations. The process of technical state changes...
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Positron scattering on molecular hydrogen: Analysis of experimental and theoretical uncertainties
PublikacjaExperiments performed in recent years on positron scattering from molecular hydrogen indicated a rise of the total cross section in the limit of zero energy, but essentially disagree on the amplitude of this rise. Mitroy and collaborators [J.-Y. Zhang et al., Phys. Rev. Lett. 103, 223202 (2009)] predicted a scattering length somewhat different from values deduced experimentally. Using a Markov chain Monte Carlo modified effective...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublikacjaIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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The Smith-Watson-Topper parameter and fracture surface topography relationship for additively manufactured 18Ni300 steel subjected to uniaxial variable-amplitude loading
PublikacjaIn this paper, the association between Smith-Watson-Topper (SWT) parameter and fracture surface topography is studied in additively manufactured maraging steel exposed to variable-amplitude fatigue loading. The post-failure fracture surfaces were examined using a non-contact 3D surface topography measuring system and the entire fracture surface method. The focal point is on the correspondence between fatigue characteristics, articulate...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublikacjaTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Improving Clairvoyant: reduction algorithm resilient to imbalanced process arrival patterns
PublikacjaThe Clairvoyant algorithm proposed in “A novel MPI reduction algorithm resilient to imbalances in process arrival times” was analyzed, commented and improved. The comments concern handling certain edge cases in the original pseudocode and description, i.e., adding another state of a process, improved cache friendliness more precise complexity estimations and some other issues improving the robustness of the algorithm implementation....
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Towards Improving Optimised Ship Weather Routing
PublikacjaThe aim of the paper is to outline a project focusing on the development of a new type of ship weather routing solution with improved uncertainty handling, through better estimation of ship performance and responses to sea conditions. Ensemble forecasting is considered to take into account the uncertainty levels that are typical of operations in a stochastic environment. Increased accuracy of weather prediction is achieved through...
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Isothermal Calorimetry and Compressive Strength Tests of Mortar Specimens for Determination of Apparent Activation Energy
PublikacjaThe hydration process of cementitious materials involves a thermally activated reaction that depends on the composition of the mixture and the curing temperature. The main parameter affecting the temperature variation of cast-in-place concrete is the apparent activation energy, which can be used for the efficient prediction of the temperature evolution and maturity index of hardening concrete. This paper discusses two methods to...
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The influence of global climate change on the environmental fate of anthropogenic pollution released from the permafrost
PublikacjaThis article presents a review of information related to the influence of potential permafrost degradation on the environmental fate of chemical species which are relased and stored, classified as potential influence in future Antarctic environment. Considering all data regarding climate change prediction, this topic may prove important issue for the future state of the Antarctic environment. A detailed survey on soil and permafrost...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublikacjaDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublikacjaDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Early warning models against bankruptcy risk for Central European and Latin American enterprises
PublikacjaThis article is devoted to the issue of forecasting the bankruptcy risk of enterprises in Latin America and Central Europe. The author has used statistical and soft computing methods to program the prediction models. It compares the effectiveness of twelve different early warningmodels for forecasting the bankruptcy risk of companies. In the research conducted, the author used data on 185 companies listed on the Warsaw Stock Exchange...
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Navier number and transition to turbulence
PublikacjaThe motivation behind this article is to explain a role of the Navier number (Na -dimensionless slip-length) in prediction of closures for laminar to turbulent transition undergoing via eddies detachment from the slip layer in nano-cannals. Additionally the role of the Navier number Na in universal modeling of phenomenon of enhanced mass flow rate reported in micro- and nano-channels has been explained. The Na number should be...
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The green waterfront of a city. Where are the limits of good planning? Gdansk case
PublikacjaThe aim of the article is to present the role of green public areas of waterfronts in shaping the image of cities, and the threats to such landscape which may be caused by wrong planning decisions. The case study of Gdansk sea-shore area in Poland is presented as an example to illustrate the values and potential of the waterfront landscape which can be easily destroyed by inadequate spatial development. Some theoretical studies...
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ASSESSMENT OF UNDERPOWER ED PROPULSION MACHINERY IN ELECTRICALLY DRIVEN SMALL INLAND WATERWAY PASSENGER SHIPS FROM CLASSIFICATION SOCIETY POINT OF View
PublikacjaPaper presents short operat ional a nd engineering analysis of underpowered propulsion in small electrically propelled small inland passenger ships. There is evidence that in certain weather conditions the phenomena of added aerodynamic resistance of small water crafts may have serious influence on their speed and manoeuvrability. Existing regulations like class societies rules for ship classification and construction or EU Directive 2006/87/EC do...